Parameters

Parameters are read-only configuration values that feed into pipeline nodes. They are defined using Param<T>, a thin wrapper that implements the Dataset trait.

How Param works

#[derive(Debug, Serialize, Deserialize)]
pub struct Param<T: Clone>(pub T);

Param implements Dataset with:

• LoadItem = T — returns a clone of the inner value
• SaveItem = () — writing is forbidden; the pipeline validator rejects any node that writes to a Param
• Error = Infallible — loading always succeeds

Because is_param() returns true, the viz dashboard and pipeline check treat parameters differently from regular datasets.

Nested parameters

Parameters can be organized into nested structs for clarity. Each struct level must derive Serialize and Deserialize:

#[derive(Serialize, Deserialize)]
struct ModelParams {
    learning_rate: Param<f64>,
    epochs: Param<u32>,
}

#[derive(Serialize, Deserialize)]
struct Params {
    model: ModelParams,
    verbose: Param<bool>,
}

# params.yml
model:
  learning_rate: 0.01
  epochs: 100
verbose: true

Nested parameters can be overridden from the CLI with dot notation:

$ my_app run --params model.learning_rate=0.001

Struct parameters

Param<T> works with any T: Clone + Serialize + Deserialize, including custom structs:

#[derive(Clone, Debug, Serialize, Deserialize)]
struct BaselinePeriod {
    start_month: u32,
    end_month: u32,
}

#[derive(Serialize, Deserialize)]
struct Params {
    baseline: Param<BaselinePeriod>,
}

baseline:
  start_month: 1
  end_month: 12

When a node loads this parameter, it receives the full BaselinePeriod struct as its argument.

no_std

Param is available in no_std environments — it requires no feature flags and uses no allocation. Only T: Clone + Serialize is needed.